The Dangers of Machine Translation

For many businesses looking to cut translation costs, machine translation can seem a tempting option. However, although machine translation may initially be cheaper, the issues machine translation causes are much more costly in the long run. Here’s why.

Man vs Machine Translation: The Continued Debate

Machine translation is gaining speed, whether we are ready for it or not. The advancements in the technology behind it is making companies increasingly invest in MT.

Can you speak the language of AI?

AI has become a helpful resource to the language field, being used to help translation between languages, but can it replace humans?

The Fate of Language Diversity in a Neural MT World

At this point, there is no real question as to whether or not Earth’s language diversity is dwindling, as it already clearly is. But there is a question as to how much of this phenomenon is due to increasingly powerful machine translation (MT) tools such as neural machine translation (NMT) versus how much is due to natural processes.

Machine Translations Will Improve the Industry’s Efficiency, But Can’t Replace Humans Yet

Machine translation is improving, but can it replace humans?

When Google Translate was introduced 10 years ago, the program was run using Phrase-Based Machine Translation (PBMT). This algorithm would split a sentence into terms and phrases, and then translate each component individually.

The 3 Models of Crowdsourced Translation

What do Wordpress, Linux, and Firefox all have in common? All of these successful projects are the result of crowdsourced contributions. As the Internet continues to connect us, collaborating on projects has become easier than ever. Even in the localization industry, crowdsourced translation solutions are helping to make translation services available to everyone and the advent of new technologies has brought about a few different methods of collaborative translation projects. Let’s take a look at three of the most popular models of crowdsourced translations.

Crowdsourcing and the Future of Translation

Advances in technology are constantly changing the way we live and, when it comes to translation, this is no different. Gone are the days of flipping through an old ‘Spanish to English’ dictionary, looking up every word in a sentence, and trying to form something that vaguely resembles a translation. Now it is much more common practice to just copy & paste the sentence into your favored machine translation service and instantly receive a more accurate and efficient result. These developments will continue to drastically change the future of translation, not just due to increasing levels of technology but also, through the emergence of platforms in which bilinguals around the world can contribute freely by translating pieces of text – crowdsourcing.

The Pitfalls of Translation Memory

Translation Memory (TM) is a database that stores language “segments” (phrases, clauses, headings, etc.) that you or your company has translated. As you continue translating documents, the database offers up translation suggestions based on those stored segments.

How Translation Memory Works - Simply CSOFT

A Look At How Translation Memory Works

Translation memory is an important tool in the modern translator’s toolkit, and one that is currently the focus of a great deal of discussion in the translation and localization community. Simply put, translation memory is a type of shared database that stores translations and continually updates itself as its users work.

Machine Translation: How Does It Work?

Machine Translation (or MT) is the ability of a computer to translate and render one language into another, without human contribution. We look a little deeper into Machine Translations different classification and types.

A Company that has Utilized MT for Big Success

In this case study we find out about companies that have utilized machine translation for great success in the translation industry.

Machine Translation Companies That Have Made It Big

Many of the ideas underlying machine translation (MT) have been around for hundreds of years, but it wasn’t until the middle of the last century that the field of “machine translation” truly came into being.